Sheldon County is a podcast that will never sound the same twice. Every time someone listens to it, they’ll begin by typing a random number into a website. This “seed” will set in motion a Rube Goldberg machine of calculation that will create characters, relationships, jealousies, betrayals, and maybe even a murder or two. These plot points will be turned into a text narrative, read aloud by a voice synthesizer, and then zipped up into an audio file. Each time it will be a unique version of Sheldon County’s story. A podcast made just for you.

That’s the dream anyway — the current execution still needs work. So far, only a few episodes of this procedurally generated podcast exist (you can listen to two below), and its creator, PhD student James Ryan, is still working on a website. He says the back-end software is mostly finished, but a few finishing touches are needed, like creating a program to automatically add the music to each episode. “Right now I’m proving the concept,” he tells The Verge. “And then I’ve got a dissertation to start.”

In other words, it might be a while.

...See, for example, video games with generative elements like No Man’sSky, which created unique planets for each player to explore; and Middle-earth: Shadow of War, which made enemies with elaborate histories that fascinated players as much as the game’s story.

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For Ryan, Sheldon County is the latest step in a life-long quest to build computers that generate fictional worlds. He’s a linguist turned programmer, whose work with the Expressive Intelligence Studio at the University of California, Santa Cruz is dedicated to finding new ways to use machines expressively.

From this simple start, Ryan made ever more complex world-generators. Sheldon Countyitself is built on a program of his called Hennepin, which creates characters, their social networks, and the world they live in. Ryan compares Hennepin to “the biggest Excel spreadsheet in the world,” with endless rows of cells that correspond to characters, traits, relationships, professions, and so on.

...1980s... “It was initially because computers at the time didn’t have much storage, so you couldn’t ship gigantic games,” he explains. “That meant it was incumbent on early titles, like Rogue, NetHack, and so on, to generate mazes on CPUs using some very fast and cheap algorithms.”

What’s interesting, though, is that modern AI techniques like deep neural networks aren’t actually that well-suited for projects like Sheldon County. Ryan says he mainly uses what’s sometimes called symbolic AI or, pejoratively, “good old-fashioned AI.” This approach is less about mining data to look for patterns, as with deep learning, and more about creating sets of rules and logical instructions that guide a process.

...He suggests Ryan’s project is interesting not necessarily because of the narratives it creates, but because it questions our idea of what a podcast is and what makes one good in the first place.